In addition to these studies, which aim directly at creating an overview of data sets, there are also studies that focus primarily on different research questions, but also contain such an overview. [1]} presented their work, which also comes in an online version briefly mentioned in the following subsection, that investigated the research question of Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving.
Yet, the authors also examined multi-modal data sets, with the multimodality referring to the sensors used. Compared to the works of Yin and Berger and Laflamme et al. however, this collection is much smaller in scope. [2]} takes on the topic of corner cases in highly automated driving. Here, too, a section revolves solely around suitable data sets for corner case detectors.
Finally, in the same year [3]} was published that contains a survey addressing data sets for monocular 3D detection. Yet, these papers also lag behind in scope. It is important to note, that publications which do not focus on data sets but provide overviews of them as side effect typically focus strongly on their area of research. Thus, they rarely provide a broad picture of data sets and tend to focus either on popular and well known data sets or their specific niche.
